rspb.royalsocietypublishing.org

ResearchCite this article: Romeralo M, Skiba A,

Gonzalez-Voyer A, Schilde C, Lawal H, Kedziora

S, Cavender JC, Glockner G, Urushihara H,

Schaap P. 2013 Analysis of phenotypic

evolution in Dictyostelia highlights

developmental plasticity as a likely

consequence of colonial multicellularity. Proc R

Soc B 280: 20130976.

http://dx.doi.org/10.1098/rspb.2013.0976

Received: 16 April 2013

Accepted: 28 May 2013

Subject Areas:developmental biology, evolution,

taxonomy and systematics

Keywords:evolution of multicellularity, morphogenetic

signalling, phylogenomics, phototropism,

encystation, sporulation

Author for correspondence:Pauline Schaap

e-mail: p.schaap@dundee.ac.uk

†These authors contributed equally to this

study.

Electronic supplementary material is available

at http://dx.doi.org/10.1098/rspb.2013.0976 or

via http://rspb.royalsocietypublishing.org.

& 2013 The Authors. Published by the Royal Society under the terms of the Creative Commons AttributionLicense http://creativecommons.org/licenses/by/3.0/, which permits unrestricted use, provided the originalauthor and source are credited.

Analysis of phenotypic evolution inDictyostelia highlights developmentalplasticity as a likely consequence ofcolonial multicellularity

Maria Romeralo1,2,†, Anna Skiba1,†, Alejandro Gonzalez-Voyer3,Christina Schilde1, Hajara Lawal1, Sylwia Kedziora1, Jim C. Cavender4,Gernot Glockner5,6, Hideko Urushihara7 and Pauline Schaap1

1College of Life Sciences, University of Dundee, Dundee, UK2Department of Systematic Biology, Uppsala University, Uppsala, Sweden3Department of Integrative Ecology, Estacion Biologica de Donana (EBD-CSIC), Sevilla, Spain4Department of Environmental and Plant Biology, Ohio University, Athens, OH, USA5Department of Genomics, Leibniz-Institute of Freshwater Ecology and Inland Fisheries, IGB, Berlin, Germany6Institute for Biochemistry I, University of Cologne, Cologne, Germany7Faculty of Life and Environmental Sciences, University of Tsukuba, Tsukuba-shi, Japan

Colony formation was the first step towards evolution of multicellularity in

many macroscopic organisms. Dictyostelid social amoebas have used this

strategy for over 600 Myr to form fruiting structures of increasing complexity.

To understand in which order multicellular complexity evolved, we measured

24 phenotypic characters over 99 dictyostelid species. Using phylogenetic

comparative methods, we show that the last common ancestor (LCA) of

Dictyostelia probably erected small fruiting structures directly from aggre-

gates. It secreted cAMP to coordinate fruiting body morphogenesis, and

another compound to mediate aggregation. This phenotype persisted up to

the LCAs of three of the four major groups of Dictyostelia. The group 4 LCA

co-opted cAMP for aggregation and evolved much larger fruiting structures.

However, it lost encystation, the survival strategy of solitary amoebas that is

retained by many species in groups 1–3. Large structures, phototropism and

a migrating intermediate ‘slug’ stage coevolved as evolutionary novelties

within most groups. Overall, dictyostelids show considerable plasticity in

the size and shape of multicellular structures, both within and between

species. This probably reflects constraints placed by colonial life on develop-

mental control mechanisms, which, depending on local cell density, need to

direct from 10 to a million cells into forming a functional fructification.

1. IntroductionA central problem in biology is to understand how complex multicellular life

forms evolved from unicellular ancestors. In many and perhaps all cases, colony

formation may have been the first step towards multicellularity [1]. Although

higher plants and animals have converted to zygotic multicellularity, colonial or

aggregative multicellularity still occurs in many eukaryote kingdoms, such as

Chromalveolata [2], Excavata [3], Amoebozoa [4,5] and Opisthokonta [6].

We investigate molecular changes that allowed colonial organisms to

achieve greater levels of multicellular complexity. Dictyostelid social amoebas

offer unique opportunities to resolve this problem. They are a genetically

diverse group [7], which contains species that form structures of less than

100 cells and one or two cell types to species that can organize up to a million

amoebas in a fruiting body consisting of five different cell types [4,8–10]. Over

a 100 species have been isolated, which can be subdivided into four major

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groups based on small subunit (SSU) rRNA and a-tubulin

sequence data [11,12]. The genomes of species representing

the major groups are now sequenced ([7,13,14]; P. Schaap &

G. Glockner 2013, unpublished data), providing information

of genotypic evolution in Dictyostelia. To link this infor-

mation to evolution of multicellularity, phylogeny-wide

phenotypic analysis of Dictyostelia is required. Phenotypic

characters were previously collated from original species

diagnosis [11]. However, these diagnoses span a period of 150

years and are not consistent in the range, depth and accuracy

of character evaluation.

In this work, we have measured 21 traits that were partially

covered by the original diagnoses and we investigated deeper

traits, such as the alternative survival strategy of encystation,

the ability to form motile ‘slugs’ and the identity of the signals

that coordinate cell movement during aggregation and mor-

phogenesis. The dataset of phenotypic traits was submitted

to phylogenetic comparative analysis to retrace character

history and identify correlated evolution of characters.

6

2. Material and methods(a) Analysis of phenotypic characters(i) CultureFor analysis of morphology, species were cultured on non-nutri-

ent (NN) agar with pregrown Klebsiella aerogenes [15]. For other

experiments, species were co-cultured with K. aerogenes on one-

fifth standard medium or one-third lactose-peptone agar with

charcoal for robust and delicate species, respectively (EXCEL file

‘Trait_Analysis’, sheet 8).

(ii) Morphological charactersThe shape and dimensions of multicellular structures were

mostly assessed or measured in situ from agar plates, using a

Leica MZ16 stereo microscope, equipped with graticule. The

morphological characteristics of amoebas and stalks were

assessed by transferring cells and structures to a droplet of phos-

phate buffer (PB) (10 mM Na/K-phosphate, pH 6.5) on a slide

glass. Spore dimensions were measured from printed images.

Each feature was measured in 25–50 individuals of each species.

(iii) Phototaxis and phototropismAmoebas were deposited as 10 ml streaks, containing 3 � 107 or

108cells ml21 on agar and incubated under unilateral illumina-

tion. After 1–8 days, the developing structures were scored for

phototaxis or phototropism.

(iv) Effects of putative chemoattractants on developmentAmoebas were resuspended at 107 or 3 � 107cells ml21 in PB and

incubated for up to 36 h as 10 ml droplets on NN agar containing

Sp-cAMPS (Biolog, Bremen, Germany), glorin (Phoenix Pharmaceu-

ticals, Burlingame, CA), folate (Sigma) or neopterin (Fluka, Buchs,

Switzerland) with the solvents of either compound as controls.

(b) Phylogenetic comparative analyses(i) Phylogenetic inferenceThe sequences of 32 orthologous proteins were retrieved from six

dictyostelid and three amoebozoan genomes and aligned using

M-COFFEE [16]. The concatenated alignment was used to construct

a rooted Dictyostelid core phylogeny with MRBAYES v. 3.2 [17]

and RAXML in TOPALi [18]. A rooted phylogeny for all Dictyos-

telia was prepared by Bayesian inference after concatenating the

SSU rDNA alignment for all species [12] to the 32 protein align-

ment. See the electronic supplementary material, figures S4 and

S5 for details.

(ii) Ancestral state reconstructionThe SSU rDNA_32 protein phylogeny (see the electronic supple-

mentary material, figure S5) was combined with the matrices of

continuous or coded categorical characters (sheets 2 and 3 of

‘Trait_Analysis’). For continuous traits, ancestral states were

estimated by a maximum-likelihood-based method under a

Brownian motion model of evolution [19]. All traits showed

high lambda values (range 0.65–0.94), indicating that this

model provides an adequate fit to the data (see the electronic

supplementary material, table S1). For categorical traits, marginal

ancestral states were estimated using a Markov continuous time

model [20] in phytools [19]. For each trait, the fit of a model

where all transitions were set to equal values (equal probability

of gain or loss of the trait) was compared with a model where

each transition parameter could take a distinct value. The

model that provided a better fit to the data was selected using

a likelihood ratio test.

(iii) Correlation analysesCorrelated evolution of quantitative characters was determined

using phylogenetic generalized least squares (PGLS; [21]), as

implemented in the package CAIC [22]. Correlations between

all characters (continuous and categorical) were determined

using the ‘Discrete’ test [20], implemented in MESQUITE [23]. ‘Dis-

crete’ compares a model in which transitions among character

states are independent, with a model in which transition rates

depend on the state of the other character (correlated evolution).

The fit of the models is evaluated using a likelihood ratio test.

Significance ( p-values) of the log likelihood differences were esti-

mated with 100 simulations. To correct for wrongly rejected null

hypotheses in multiple comparisons, the threshold p-value for

rejecting the null hypothesis (no correlation between datasets)

was adjusted by a false discovery rate-based method [24].

3. Results(a) Phenotype analysis(i) The cellular levelGrowing amoebas are morphologically similar in all dictyos-

telids, and show filose pseudopodia, prominent food

vacuoles and contractile vacuoles [9]. Spores, which are

formed in fruiting structures, range from round to narrowly

elliptical and often contain conspicuous granules at their

poles, which are either grouped tightly (consolidated) or

loosely (unconsolidated). Continuous (quantitative) charac-

ters, such as cross-section area, length and diameter were

measured for amoebas and spores, and recalculated to yield

average diameter and eccentricity (length divided by diam-

eter). The descriptive statistics of these and all other

quantitative traits are summarized in EXCEL file ‘Trait_Analy-

sis’, sheet 2. The range of averaged values per species was

subdivided into four intervals, such that each interval con-

tained an equal number of species. These intervals, the

character states, are plotted onto the previously constructed

SSU rDNA phylogeny [12] in the electronic supplementary

material, figure S1. The states of categorical (qualitative) char-

acters were also plotted onto the phylogeny in the electronic

supplementary material, figure S1. To assess group-specific

trends in character evolution, proportional representations

of character states in each group were calculated (figure 1).

phototaxisnoweakyes no migration

none

no data

at 100 µmat 10 µmat 1 µm

inhibitory effect

pore area

0 0.2

0.4

0.6

0.8

1.0

0.2

0.4

0.6

0.8

1.0

0.2

0.4

0.6

0.8

1.0

0.2

0.4

0.6

0.8

1.0

0.2

0.4

0.6

0.8

1.0

2B2A

1

43

2B2A

1

43

2B2A

1

43

spore eccentricityamoeba diameter aggregate diameter

sorogen length sorus diameter stalk length stalk diameter base diameter

amoeba eccentricity

tip diameter

group

2B2A

1

43

2B2A

1

43

2B2A

1

43

2B2A

1

43

2B2A

1

43

spore granules aggregate shape

branching

habit

stalk tip shape stalk base shape

migration type

stalk support

migration tendency

phototaxisphototropism

encystation

on aggregationinhibitory effects of Sp-cAMPS

on culmination

spore eccentricity1–1.2

1.2–1.71.7–1.91.9–3.3

amoeba eccentricity1–1.18

1.18–1.251.25–1.341.34–1.60

aggregate diameter85–275

275–830830–1440

1440–7000

sorogen length38–190

190–275275–400400–3030

sorus diameter18–6464–9090–118

118–232stalk diameter

0.8–6.46.4–9.09.0–12.0

12.0–22.0

stalk length170–1200

1200–23002300–32003200–8200

tip diameter0.5–3.43.4–4.04.0–5.5 5.5–14.4

base diameter1–11

11–1818–2323–52

5.7–15.915.9–20.220.2–25.525.5–52.1

amoeba diameter4.0–7.67.6–8.58.5–9.59.5–17.0

spore area

spore shape and granulesglobose no granulesoblong unconsolidatedoblong consolidatedoblong no polar granulesoblong dispersed

aggregate shapemoundmound with short streamsfirst mound, then streamsstreams, breaking upstreams

branching nonelateralrepeated lateralbifurcatingsessile whorlsirregular whorlsregular whorls

capitateclavateobtuseacuminatepiliform

stalk base stalk tipconicalclavateroundacuminatecrampon

stalk supportdisksupporternone

habitcoremiformclusteredgregarioussolitary

nonerarely with stalkwith stalkfree and with stalkfree

migration type

migration tendencynoweakyes

nonesparsemoderateabundant

encystation

phototropismnoweakyes

of Sp-cAMPS

taxon

fraction

(a) (b) (c) (d) (e)

fractionfractionfractionfraction

( f ) (g) (h) (i) ( j)

(k) (l) (m) (n) (o)

(p) (q) (r) (s) (t)

(u) (v) (w)(x) (y)

Figure 1. (a – y) Fractions of character states in each major group or clade. Qualitative and quantitative features that define species phenotype were measured or inves-tigated over 99 species. For quantitative characters, the range of measured values was divided into four intervals, representing the character states. For qualitativecharacters, the states represent the observed different versions of the feature. The number of states for each character was counted for each major taxon group orclade of the Dictyostelid phylogeny [11] and divided by the number of species per group/clade. For polymorphic characters, the dominant state was counted as 2/3and the less dominant state as 1/3. The resulting fractions were plotted as stacked bar graphs in which the colours denote the different character states as indicated.

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Group 2 was subdivided in clade 2A, which contains only

acytostelids and clade 2B, which contains a mixture of poly-

sphondylids and dictyostelids. Across most characters, clade

2A was more different from clade 2B than from any other group.

Amoeba diameters range from 4 to 17 mm between

species, but there are no marked differences in amoeba

dimensions between groups (figure 1a,b). Spores were mark-

edly smaller in group 1 (figure 1c) and usually harboured

consolidated granules in groups 1 and 3, and unconsolidated

granules in clade 2B (figure 1l ). Most species in clade 2A

have round spores, whereas the oblong spores of group 4

species mostly lack prominent polar granules.

(ii) Multicellular structuresCells can either aggregate as individuals forming a mound, or

join up to form inflowing streams, which sometimes frag-

ment into accessory aggregates. Intermediate forms, where

cells first aggregate individually and then form streams, or

do both, also occur. In group 4, species always aggregate in

streams, whereas species in the other groups show a mixture

of aggregation types (figure 1m). Aggregates are on average

larger in groups 4 and clade 2B than in groups 1, clade 2A

and 3 (figure 1e). Aggregates transform into one or more

fruiting body precursors, the sorogens or slugs. Slugs are also

relatively large in groups 4 and clade 2B, and this trend con-

tinues in the dimensions of the stalk and spore head (sorus)

of the fruiting body (figure 1f–k). Despite these trends, there

is large size variation between multicellular structures within

species (see the electronic supplementary material, figure S2),

illustrating that species can accommodate greatly varying

amounts of cells within a single structure.

Sorogens either form fruiting bodies directly or migrate

horizontally, often leaving the stalk behind. Migration is

mostly absent or weak in groups 1–3 and common in group

4 (figure 1n). Fruiting body habit and branching pattern also

show group-specific trends, with group 4 species mainly form-

ing solitary, unbranched fruiting structures, while multiple

loosely (gregarious) to tightly (coremiform) grouped fruiting

bodies emerge from group 1–3 aggregates (figure 1o; electronic

supplementary material, figure S1). Lateral branching is

common in groups 1 and 3, while most clade 2B species and

two species that are intermediate to groups 3 and 4 form regu-

lar whorls of branches (figure 1p; electronic supplementary

material, figure S1).

In most Dictyostelia, the stalk consists of highly vacuo-

lated cells with a cellulose wall, except for clade 2A, where

the stalk is a cellulose tube (see the electronic supplementary

material, figure S1). The stalk tip is commonly broadened

(clavate or capitate) in groups 1 and 4, pointed (acuminate

or piliform) in clades 2A and 2B, and a mixture of those in

group 3 (figure 1q). The stalk base is usually round to conical,

but a small clade of group 3 species split the stalk in sections

to form a crampon (figure 1r; electronic supplementary

material, figure S1). Several group 4 species form a cellular

basal disc or supporter to buttress the stalk (figure 1s).

lowest effectiveconcentration (C)none

100 µM10 µM

1 µM

none

inhibiteddelayedless aggregatessmaller aggregatesstreaming lostcells leave drop

none

inhibited

deformed structures

delayedless fruiting bodiessmaller structures

type of effect (T) on aggregation (aggr.) type of effect (T) on fruiting body formation (fru.)

enlarged territoriesaccelerated

Figure 2. Disruption of aggregation and morphogenesis by putative attractants. Cells were spotted as 10 ml droplets on NN agar containing 1, 10 or 100 mM ofeither Sp-cAMPS, glorin, folate or neopterin. The progression of aggregation and fructification were recorded at 2 h intervals. The types of deviations (T) from thecontrol treatment (no additives or solvent) that occurred during aggregation (aggr.) and fructification (fru.) are separately shown in the figure by colour-codedboxes. The concentrations where deviations were first observable (C) are shown in shades of grey. Eight delicate species that only develop on charcoal agarcould not be tested, because the charcoal adsorbs the attractants. For those species and for chemoattractants that were not tested on all species, boxes retainthe beige background colour. The colour-coding of species names reflects group/clade affiliation as in the electronic supplementary material, figure S5.

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(iii) EncystationSimilar to their amoebozoan ancestors, several dictyostelids

can still encyst individually under conditions that do not

favour aggregation [9]. To investigate encystation systemati-

cally, we exposed species to stress conditions known to

trigger encystation. Because cells also died and disintegrated

in response to stress, encystation could not be quantitated pre-

cisely and we distinguish between sparse (0.1–1%), moderate

(1–20%) and abundant (20–100%) encystation. In general,

most group 2 polysphondylids and acytostelids encysted abun-

dantly (figure 1t; electronic supplementary material, figure S3).

One-third of group 1 and half of group 3 species showed sparse

to moderate encystation. Remarkably, no group 4 species could

be induced to encyst.

(iv) Phototaxis and phototropismBoth the migration of slugs and the outgrowth of fruiting

bodies are often oriented towards light. These behaviours,

termed phototaxis and phototropism, respectively, direct

the structures to the soil surface, where spores are readily dis-

persed [25]. We analysed phototaxis and phototropism by

developing species under unilateral light. Phototropism was

not observed for acytostelids in clade 2A, but about half of

clade 2B species were strongly phototropic (figure 1u; elec-

tronic supplementary material, figure S1). About 25 per

cent of group 1 and 40 per cent of group 3 species showed

strong phototropism and over 60 per cent of group 4 species.

Phototaxis requires the ability of slugs to migrate.

Migration was also scored during development under inci-

dent light (figure 1n), but was sometimes worse and

sometimes better under unilateral light. In group 4, approxi-

mately 70 per cent of species migrate strongly and these

species are all phototactic. All migrating group 3 species are

phototactic and most of the clade 2B species, but in groups

1 and clade 2A, both migration and phototaxis are weak or

absent (figure 1v,w).

(v) Use of chemoattractantThe chemoattractants for aggregation are only known for a

few species. Dictyostelium discoideum and some group 4 species

use cAMP; the Polysphondylium violaceum chemoattractant is

glorin, a modified dipeptide [26], and the Dictyostelium minutumand Dictyostelium lacteum chemoattractants were identified as

folate and neopterin, respectively [27,28]. Folate is also secreted

by bacteria, and attracts many dictyostelids to their food. cAMP

additionally coordinates cell movement during fruiting body

morphogenesis in D. discoideum [29]. Chemoattractants are

secreted at nanomolar concentrations, which renders their

identification a major challenge. However, a less stringent

method can be performed to assess whether known molecules

might be used as attractants. When incorporated in the agar at

high concentrations, they usually delay or prevent aggregation,

by disrupting the natural chemoattractant gradients.

All species were spotted on agar containing increasing con-

centrations of glorin, folate, neopterin or Sp-cAMPS. The latter

was used instead of cAMP to prevent hydrolysis by secreted

phosphodiesterases [30]. Developmental progression was

scored for deviations from normal aggregation and fructifica-

tion. Effects on aggregation ranged from time delays, less or

smaller aggregates formed, loss of streaming and movement

of cells out of the drop. The latter occurs because the cells

degrade the chemoattractant inside the drop and move

towards the higher concentration outside. If compounds

affect aggregation, subsequent multicellular development

usually suffers accordingly with less, smaller or no fruiting

bodies formed.

Sp-cAMPS inhibits aggregation of all group 4 species, but

none of the species in groups 1 and 2 (figures 1x and 2).

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Aggregation of a single group 3 species is inhibited and

of another promoted by Sp-cAMPS. Strikingly, Sp-cAMPS dis-

rupts or blocks fructification in almost all group 1–3 species

(figures 1y and 2). The other attractants exert less specific

effects on individual species and were, owing to the time-con-

suming nature of the assays, only tested on four to eight species

per taxon group (figure 2). Folate and neopterin affected about

half of the species on which they were tested in groups 1, 2 and

4, but mostly only at 100 mM. Folate was particularly effective

in disrupting aggregation of over half of group 3 species. None

of the tested group 4 species responded to glorin. However,

aggregation of P. violaceum and its two relatives, Dictyosteliumlaterosorum and Polysphondylium patagonicum, which occupy a

small clade between groups 3 and 4, was disrupted by 1 or

10 mM glorin, as was aggregation of several species in groups

1–3. There was no effect of folate, glorin and neopterin on cul-

mination that could not be attributed to an earlier effect on

aggregation. Asghar et al. [31] recently reported that four

group 1 and nine clade 2B species showed chemotaxis to

glorin, but none of three tested group 4 species. Their choice

of species partially overlaps with ours, and both studies con-

firm each others results.

(b) Evolutionary analysis(i) Phylogeny reconstruction from 32 proteinsA reliable phylogeny is of primary importance to retrace pheno-

typic evolution. The earlier SSU rDNA and b-tubulin-based

phylogenies subdivided dictyostelids into the same grouping,

but did not agree about the root of the tree, with rDNA pointing

to group 1 and a-tubulin to group 2 as the earliest diverging

group [11]. A phylogeny inferred from 33 proteins from species

with sequenced genomes, indicated that the root was placed

between groups 2 and 4, but this analysis lacked group 3

sequences and used very distant taxa as outgroup [7]. Mean-

while, three more dictyostelid genomes have been sequenced:

Dictyostelium purpureum (Dpur) from group 4 [14], D. lacteum(Dlac) from group 3 (http://sacgb.fli-leibniz.de/cgi/index.pl)

and Acytostelium subglobosum (Asub) from clade 2A (http://

acytodb.biol.tsu kuba.ac.jp/). Additionally, Amoebozoan gen-

omes became available that provide less distant outgroup

sequences, such as the genomes of Entamoeba histolytica[32], Acanthamoeba castellani [33] and Physarum polycephalumhttp://genome.wustl.edu/geno mes/view/physarum_poly-

cephalum. We retrieved orthologues for all or most of the 32

genes of the previous set of 33 genes from the six dictyostelid

and three amoebozoan genomes and prepared a concatenated

alignment of about 18 180 amino acids, which was subjected

to different methods for phylogenetic inference. All methods

robustly placed the root between two branches that contain

groups 1 and 2, and groups 3 and 4, respectively (figure 3a; elec-

tronic supplementary material, figure S4a–e,o). This topology

was also produced using three out of four concatenated sets of

seven of the shorter proteins (see the electronic supplementary

material, figure S4f,h,i), but by only two of the four remaining

larger proteins (see the electronic supplementary material,

figure S4j,m), while SSU rDNA yielded the same topology (see

the electronic supplementary material, figure S4n) as previously

[11]. The E. histolytica sequences diverged strongly from the other

amoebozoan sequences, possibly owing to its anaerobic, para-

sitic lifestyle. Deleting these sequences did not affect the

rooting (see the electronic supplementary material, figure S4e)and they were omitted from subsequent inference of a

phylogeny for all Dictyostelia. This phylogeny was inferred

from the earlier alignment of the SSU rDNAs of all species

[11,12], concatenated to the 32 protein alignment of the group-

representative and outgroup species (see the electronic sup-

plementary material, figure S5). It retains almost the same

ordering of species within the four major groups as the earlier

SSU rDNA phylogenies [11,12], but the root is now placed

between two branches that contain groups 1,2 and groups

3,4. One of two group-intermediate species, Dictyosteliumpolycarpum, which was previously located between groups 2

and 3, is now a sister species to group 2. This is probably

not artefactual, since D. polycarpum displays morphological fea-

tures, such as unconsolidated spore granules and pointed stalk

tips that are characteristic features of group 2 (see the electronic

supplementary material, figure S1).

(ii) Ancestral state reconstructionThe newly inferred phylogeny was combined with the charac-

ters measured in this work to infer the phenotypes of the

last common ancestors (LCAs) of major groupings. Ancestral

states for continuous traits were reconstructed using a

method based on maximum likelihood [19] and are listed in

‘Trait_Analysis’, sheet 6. The ancestral state values for spore,

sorogen and fruiting body dimensions at major nodes of the

phylogeny are graphically represented in figure 3c. The infer-

ence shows that the LCA to all Dictyostelia formed relatively

small sorogens and fruiting bodies. The LCAs to groups 1–3

retained their small size, but the group 4 LCA increased fruit-

ing body size about 2.5-fold (figure 3c). However, within each

group, except for clade 2A, larger forms emerged, as illustrated

for sorus diameter in figure 3b.

For categorical characters, we estimated ancestral states

using a Markov continuous time model [20]. For each charac-

ter, the proportional likelihoods of ancestral states are plotted

as pie sections onto the phylogeny (see the electronic supple-

mentary material, figure S6a–p). For several labile characters,

such as aggregate and stalk base shape (see the electronic

supplementary material, figure S6b,h), the ancestral states at

many major nodes are equivocal, presenting roughly equal

likelihoods for all different states. Characters for which ancestral

states at major nodes could be inferred with 60–100% proba-

bility are summarized in figure 3c. The LCA to all Dictyostelia

formed unbranched grouped fruiting bodies (see the electronic

supplementary material, figure S6d,e), with a cellular stalk and

broadened stalk tip (see the electronic supplementary material,

figure S6g,i). Its spores were elliptical and contained polar gran-

ules (see the electronic supplementary material, figure S6a).

It used cAMP to coordinate fruiting body morphogenesis

(see the electronic supplementary material, figure S6p), but

not aggregation (see the electronic supplementary material,

figure S6o), which may have been mediated by glorin (see the

electronic supplementary material, figure S6n; [31]).

Except for the broadened stalk tip, these character states

persisted into major branches I and II, and into the LCAs of

groups 1–3. The LCA to group 2 gained pointed stalk tips,

while the LCA to clade 2A also gained an acellular stalk.

The LCA of clade 2B adorned its fruiting bodies with regular

whorls of side branches, while the LCA of clade 2A lost polar

spore granules. The group 4 LCA also lost polar spore gran-

ules, while its sorogens acquired migratory behaviour and its

amoebas used cAMP for aggregation. It should be noted that

all inference of ancestral states reflects probable trends in trait

0.1

Dpur-4

Dfas-1Asub-2A

Ehis

Dlac-3

PhyP

Ddis-4

Acas

Ppal-2B1

1

11

1

11

(a) (b)

(c)

(µm)18–6464–9090–118

118–232LCA I II

1 24

3

2A2B sorus

diameter

D. brefeld

D. robustu

m

D. austra

D. caveatum

D. granul

D. oculare

A. anast

A. subglob

D. antart

D. deminut

group 2

III

LCA

Sp-cAMPS

glorin

glorin?

glorin

glorin

glorin

glorin

clade 2B group 4group 1 clade 2A group 3

glorin?glorin?

Sp-cAMPS

Sp-cAMPS

Sp-cAMPS

Sp-cAMPS

Sp-cAMPS

Sp-cAMPS

Sp-cAMPS

Sp-cAMPS

Sp-cAMPS

0.5 mm

glorinSp-cAMPSSp-cAMPS

stalk stalk tipacellular

cellular pointed

broadened

compounds disrupting

branching

habitgrouped

yesno

solitary

none regular

culminationaggregation

sorogen

migration5µm

none

unconsolidatedconsolidated

spore granules

whorls

0.1 mm

0.1 mm

Figure 3. Phylogeny correction and ancestral state reconstruction. (a) Genome-based core phylogeny. The sequences of 32 orthologous proteins in six group- or clade-representative Dictyostelid taxa (Ddis/Dpur—group 4, Dlac—group 3, Ppal—clade 2B, Asub—clade 2A, Dfas—group 1) and three outgroup taxa Ehis, Acas and PhyPwere retrieved from genome sequencing projects, aligned and concatenated. The full alignment and subsets thereof (see the electronic supplementary material, figure S4)were subjected to Bayesian inference for phylogeny reconstruction [17]. Bayesian posterior probabilities of nodes are indicated. Scale bar: number of substitutions per site.(b) Character evolution. All measured characters were combined with the newly inferred phylogeny for all Dictyostelia (see the electronic supplementary material, figure S5)and subjected to inference of character history and ancestral state reconstruction using maximum-likelihood-based methods. The analysis of quantitative characters is listedin EXCEL file ‘Trait_Analysis’, sheet 6 and of categorical characters in the electronic supplementary material, figure S6a – p. For graphical representation of the evolutionaryhistory of the character ‘sorus diameter’, the range of calculated values was subdivided into four intervals, which, represented by shades of blue, were plotted onto thephylogeny. (c) Ancestral states at major nodes. For quantitative characters, the state values at nodes that connect major branches (highlighted in colour in ‘Trait_Analysis’,sheet 6) were used to draw fruiting body, slug and spore dimensions at the correct relative sizes onto a schematic of the deep topology of the Dictyostelid phylogeny. Onlystalks are presented at one-third of their length, relative to diameter. For all categorical characters that showed a well-defined character history, character states at majornodes were retrieved from the electronic supplementary material, figure S6 and plotted as cartoons onto the phylogeny.

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evolution, which inevitably involves uncertainty, and not a

definitive trait history.

(iii) Correlated character evolutionTo gain initial insight into possible common causes for charac-

ter evolution and causal relationships between characters, we

investigated to what extent changes in individual characters

are correlated. Standard statistical correlation methods are

not appropriate, because species have varying degrees of

shared ancestry and cannot be considered as independent

samples [34–36]. To assess correlations between continuous

characters, we used PGLS [21], which estimates an evolution-

ary parameter, lambda, simultaneously with the regression

parameters that provides the necessary correction of trait

covariance based on the phylogenetic signal of the data [35,36].

The most obvious set of positively correlated traits are the

dimensions of aggregates, sorogens and various parts of

the fruiting body as the sorus, stalk and stalk base (see the

electronic supplementary material, table S2). This is not surpris-

ing since large aggregates will normally give rise to large

fruiting structures, unless they split up to form multiple

sorogens. There is a weak positive correlation between the size

of spores and the size of amoebas, and between the size of

either amoebas or spores and the size of multicellular structures.

The variance in amoeba size explains 12 per cent of the variance

in spore size and 4–13% of the size variance in multicellular

structures. This suggests that amoeba size contributes to the

size of spores and structures, but is not the major determinant.

The categorical characters form a much larger dataset and

to correlate these characters with each other and with the con-

tinuous characters, we used Pagel’s ‘Discrete’ test [20], which

compares the difference between the log likelihoods of a

model where the rates of change in each character are inde-

pendent of the state of the other and a model where rates

of change depend on the state of the other character. The

method is only applicable to binary characters, and we there-

fore transformed multiple and continuous states into binary

polar granulesconsolidated gran.

non-consolid. gran.spore area

spore eccentricityamoeba diameter

amoeba eccentricity

aggregate diameter

streamsmounds

slug lengthsorus diameter

stalk lengthstalk diameter

stalk volumetip diameter

base diameterbroadened tip

pointed tipcrampon base

cellular supportcellular stalk

clustered habitsolitary habit

branching dominantlateral branching

sessile whorlsirregular whorls

regular whorlsmigration

phototaxisphototropism

encystationcAMP disrupts agg.

pola

r gr

anul

esco

nsol

idat

ed g

ran.

non-

cons

olid

. gra

n.sp

ore

area

spor

e ec

cent

rici

tyam

oeba

dia

met

eram

oeba

ecc

entr

icity

aggr

egat

e di

amet

er

stre

ams

mou

nds

slug

leng

thso

rus

diam

eter

stal

k le

ngth

stal

k di

amet

erst

alk

volu

me

tip d

iam

eter

base

dia

met

erbr

oade

ned

tippo

inte

d tip

cram

pon

base

cellu

lar

supp

ort

cellu

lar

stal

kcl

uste

red

habi

tso

litar

y ha

bit

bran

chin

g do

min

ant

late

ral b

ranc

hing

sess

ile w

horl

sir

regu

lar

who

rls

regu

lar

who

rls

mig

ratio

nph

otot

axis

phot

otro

pism

ency

stat

ion

cAM

P di

srup

ts a

gg.

Figure 4. Correlated character evolution. To assess which characters evolved together, the dictyostelid phylogeny was combined with a character matrix that wasreconfigured to express all characters in binary form (‘Trait_Analysis’, sheet 4). The ‘Discrete’ correlation test [20] was run with 10 iterations to estimate the loglikelihood difference (Likdif ) between alternative models of correlated and uncorrelated evolution, and 100 simulations to estimate p-values, when appropriate (seethe electronic supplementary material, figure S7). Strong positive and negative correlations ( p ¼ 0; Likdif . 10) are highlighted in amber and dark blue, respect-ively. Weak positive and negative correlations ( p , 0.03; Likdif , 10) are highlighted in light yellow and light blue, respectively.

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expressions. In essence, this subdivides continuous charac-

ters into two states: small (0) and large (1), while categorical

character states become separate characters with states

absent (0) and present (1). The correlation matrix is listed in

‘Trait_Analysis’, sheet 7 and is summarized in figure 4.

The strong positive correlations between the dimensions

of multicellular structures that were detected with PGLS are

also found with ‘Discrete’, indicating that the reduction

from continuous to binary character states has no profound

effect on the outcome of the analysis. Large size of structures

is negatively correlated with a clustered habit, consolidated

spore granules and encystation. Mostly, size is not or nega-

tively correlated with dominant branching. However, stalk

length is positively correlated with the formation of regular

whorls of branches. Interestingly, the size of structures is

positively correlated with cAMP-mediated streaming aggre-

gation and with the cellular stalk, slug migration, phototaxis

and phototropism, with the latter two features very strongly

correlated with each other.

4. Discussion(a) Robust sporulation from loosely controlled

morphogenesisThe traitmap of all measured characters (see the electronic

supplementary material, figure S1) shows a fairly scattered

distribution of character states over the tree with many

states reappearing multiple times in different clades. This is

particularly the case for features that describe the size and

shape of aggregates, slugs and fruiting bodies. Most species

are also individually polymorphic for these characters (see

‘Trait_Analysis’, sheet 3, columns Q–X). Depending on

local conditions of cell density, individual species can make

aggregates and fruiting bodies in a wide range of sizes.

Even when developed under standardized conditions, indi-

vidual structures from the same species easily show a

fourfold difference in size (see the electronic supplementary

material, figure S2). At low food availability, even a fairly

large species, such as Polysphondylium pallidum, can form

fruiting bodies from as few as seven cells [8].

The morphology of structures also varies depending on

cell density. Species, which normally have clustered or

branched fruiting bodies show solitary and unbranched

phenotypes when developing from small numbers of cells,

while normally solitary and unbranched species show some

clustering and branching at high cell density.

There is good evidence that fruiting body morphogenesis

in D. discoideum, and representative taxa from all four groups

is coordinated by cAMP pulses that are emitted by the tips of

sorogens and propagate through the structure as standing or

spiral waves [29,37–40]. This is likely to be case for all Dic-

tyostelia, since we show in this work that Sp-cAMPS, which

desensitizes cells to cAMP pulses, disrupts fruiting body

morphogenesis in almost all investigated species (figure 2).

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cAMP pulses are produced by positive and negative feedback

of cAMP on its own synthesis [41,42]. The output dynamics

of this network, such as wave form and suppression of com-

peting oscillators, which govern the size and shape of fruiting

structures, are easily affected by genetic variation in the com-

ponent proteins and naturally occurring physico-chemical

factors [43–45]. Such variables can account both for morpho-

logical variation between species and within species upon

exposure to different conditions. This environmentally adap-

tive system for morphogenetic control and the consequent

plasticity of forms that it generates is eminently suited for

organizing variable numbers of cells into functional units.

However, it contrasts strongly with the superimposed layers

of genetic control that shape the body plan of higher animals,

where, for obvious reasons, extensive plasticity in the size

and shape of organs and appendages is mostly detrimental.

(b) Trends in the evolution of phenotypeDespite morphological plasticity, there are trends in dictyos-

telid phenotypic evolution. Ancestral state reconstruction

showed that the LCA to all Dictyostelia as well as the LCAs

of the two major branches and groups 1–3 probably had

small, unbranched fruiting structures, containing elliptical

spores with polar granules. cAMP was probably used to

coordinate fruiting body morphogenesis, but not aggrega-

tion, which could have been mediated by glorin (figure 2;

[31]). The LCA to clade 2B evolved fruiting structures with

regular whorls of side branches, whereas the group 4 LCA

formed large unbranched fruiting bodies. It lost spore gran-

ules, but gained cAMP as attractant for aggregation. Slug

migration, phototaxis and phototropism evolved several

times independently within most major groups.

Correlation analysis highlights coevolution of large,

solitary, unbranched multicellular structures, streaming aggre-

gation, slug migration, phototaxis and phototropism, and use

of cAMP as attractant (figure 4). The analysis can identify char-

acters that evolved together, but not why this is the case.

However, occasionally correlated features can reveal hints

into underlying causes. This is, for example, the case for the

strong positive correlation between fruiting bodies size and

phototropism. This correlation does not only exist between

species, but also within phototropic species; smaller fruiting

bodies are less phototropic [46]. If phototropism depended

on a specialized sensor, there is no reason why small structures

should lack phototropism. Bonner et al. [47] proposed that

ammonia, produced in response to light focused by the tip at

the distal side of the slug, locally speeds up cell movement

and causes the tip to veer towards the light. This can explain

the size dependency of phototropism, since build-up of

ammonia in small sorogens would be limited due to dissipa-

tion into the atmosphere. Slug migration and phototaxis are

also strongly correlated with size between species, and this is

also the case within species [48]. Lack of slug migration and

light responsiveness could therefore be a consequence of the

small size of species.

A more enigmatic relationship that was already noted in

the 1970s [49] is the correlation between gain of cAMP as attrac-

tant and loss of polar spore granules and encystation. The early

workers also associated polar granules with smaller, branched

or clustered fruiting structures, as substantiated in this work

(figure 4). It can be envisaged that more robust fructifica-

tion made encystation superfluous, but why this should be

connected with spore granules and cAMP is unclear. The

answers may come from the function and ontogeny of spore

granules and more importantly from the ecological factors

that acted on the gain and loss of all these features. These fac-

tors, contained in the habitat, geographical origin and local

climate conditions of species and their interactions with other

organisms in the rhizosphere provide the ultimate cause for

phenotypic innovation. However, their influence is at present

difficult to address, owing to sparse sampling of most species

and limited information on their lifestyles in nature.

The future aim of our work is to identify causal relation-

ships between the evolution of multicellularity and the

evolution of genes and genomes. Bioinformatic and exper-

imental approaches are being used to analyse changes in

content, regulation and function of developmental control

genes between the recently sequenced genomes of species

representing all major groups of Dictyostelia. Combined

with the opportunity to replace genes in both late and early

diverging species with more ancestral or derived alleles,

respectively, such approaches have already yielded insight

into the evolutionary history of cAMP signalling [50] and

can ultimately identify the critical genetic modifications that

caused the emergence of multicellular life forms.

Acknowledgements. M.R. measured morphological traits, A.S. measuredbehavioural traits with contributions from C.S. and S.K. A.G.V., P.S.and M.R. performed data analysis, H.L., G.G. and P.S. constructedthe 32 protein phylogeny, J.C.C. contributed novel species, G.G.and H.U. contributed genomic data and P.S. wrote the manuscript.We thank the Physarum http://genome.wustl.edu/genomes/view/physarum_polycephalum and Acanthamoeba genome projectshttp://blast.hgsc.bcm.tmc.edu/blast.hgsc?organism=AcastellaniNefffor DNA sequences. We are grateful to Dr Tom Walsh for guidancewith cluster computing.

Funding statement. This work was financially supported by Biotechnol-ogy and Biological Sciences Research Council grants nos BB/D013453/1, BB/E016308/1, BB/G020426/1 and the WellcomeTrust grant no. 090276. M.R. was additionally supported by EUMarie Curie grant no. PIEF-GA-2009-236501.

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